Towards Adjusting Mobile Devices to User’s Behaviour

Autor:	Katharina Morik, Nico Piatkowski, Marco Stolpe, Felix Jungermann, Olaf Spinczyk, Jochen Streicher, Peter Fricke
Rok vydání:	2011
Předmět:	Basis (linear algebra) business.industry Computer science Embedded system Available energy Bandwidth (computing) Operating system level business Special class Mobile device Power (physics)
Zdroj:	Lecture Notes in Computer Science ISBN: 9783642235986 MSM/MUSE
DOI:	10.1007/978-3-642-23599-3_6
Popis:	Mobile devices are a special class of resource-constrained embedded devices. Computing power, memory, the available energy, and network bandwidth are often severely limited. These constrained resources require extensive optimization of a mobile system compared to larger systems. Any needless operation has to be avoided. Timeconsuming operations have to be started early on. For instance, loading files ideally starts before the user wants to access the file. So-called prefetching strategies optimize system's operation. Our goal is to adjust such strategies on the basis of logged system data. Optimization is then achieved by predicting an application's behavior based on facts learned from earlier runs on the same system. In this paper, we analyze system-calls on operating system level and compare two paradigms, namely server-based and device-based learning. The results could be used to optimize the runtime behaviour of mobile devices.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::7c2b3a14480abb2b79e37d8f202d951b https://doi.org/10.1007/978-3-642-23599-3_6 Zobrazit plný text záznamu